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lookout
View on CRAN: Click
here
Download and install lookout package within the R console
Install from CRAN:
install.packages("lookout")
Install from Github:
library("remotes")
install_github("cran/lookout") Install by package version:
library("remotes")
install_version("lookout", "2.0.0") Attach the package and use:
library("lookout")
Maintained by
Sevvandi Kandanaarachchi
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-02-12
Latest Update: 2022-10-14
Description:
Outlier detection using leave-one-out kernel density estimates and
extreme value theory. The bandwidth for kernel density estimates is computed
using persistent homology, a technique in topological data analysis. Using
peak-over-threshold method, a generalized Pareto distribution is fitted to
the log of leave-one-out kde values to identify outliers.
How to cite:
Sevvandi Kandanaarachchi (2021). lookout: Leave One Out Kernel Density Estimates for Outlier Detection. R package version 2.0.0, https://cran.r-project.org/web/packages/lookout. Accessed 15 Jul. 2026.
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Complete documentation for lookout
Functions, R codes and Examples using
the lookout R package
Some associated functions: autoplot.lookoutliers . autoplot.persistingoutliers . lookout-package . lookout . lookout_ts . persisting_outliers . reexports .
Some associated R codes: autoplot_lookout.R . autoplot_persistence.R . lookout-package.R . lookout_ts.R . lookoutliers.R . outlier_persistence.R . print.R . utils.R . Full lookout package functions and examples
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